← fal.ai

Add Request to Queue with fal.ai API

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Add Request to Queue with the fal.ai API
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Getting Started

Create a workflow to Add Request to Queue with the fal.ai API. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

  1. Configure the Add Request to Queue action
    1. Connect your fal.ai account
    2. Configure App ID
    3. Configure Data
    4. Optional- Configure Rerun Enabled
  2. Select a trigger to run your workflow on HTTP requests, schedules or app events
  3. Deploy the workflow
  4. Send a test event to validate your setup
  5. Turn on the trigger

Integrations

Add Request to Queue with fal.ai API on New Requests (Payload Only) from HTTP / Webhook API
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Add Request to Queue with fal.ai API on New Submission from Typeform API
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Add Request to Queue with fal.ai API on New Submission (Instant) from Jotform API
Jotform + fal.ai
 
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Add Request to Queue with fal.ai API on New Scheduled Tasks from Pipedream API
Pipedream + fal.ai
 
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Add Request to Queue with fal.ai API on New Download Counts from npm API
npm + fal.ai
 
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Details

This is a pre-built, source-available component from Pipedream's GitHub repo. The component is developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Add Request to Queue on fal.ai
Description:Adds a request to the queue for asynchronous processing, including specifying a webhook URL for receiving updates. [See the documentation](https://fal.ai/docs/model-endpoints/queue#queue-endpoints).
Version:0.0.1
Key:fal_ai-add-request-to-queue

Code

import app from "../../fal_ai.app.mjs";

export default {
  key: "fal_ai-add-request-to-queue",
  name: "Add Request to Queue",
  description: "Adds a request to the queue for asynchronous processing, including specifying a webhook URL for receiving updates. [See the documentation](https://fal.ai/docs/model-endpoints/queue#queue-endpoints).",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    appId: {
      propDefinition: [
        app,
        "appId",
      ],
    },
    data: {
      type: "object",
      label: "Data",
      description: "Additional data to include with the request. [See the documentation](https://fal.ai/models/fal-ai/lora/api#schema-input) for more input fields.",
      default: {
        model_name: "stabilityai/stable-diffusion-xl-base-1.0",
        prompt: "Photo of a european medieval 40 year old queen, silver hair, highly detailed face, detailed eyes, head shot, intricate crown, age spots, wrinkles",
      },
    },
    reRunEnabled: {
      type: "boolean",
      label: "Rerun Enabled",
      description: "Enable the step to rerun to retrieve the request response. [See the documentation](https://pipedream.com/docs/code/nodejs/rerun/#flowrerun).",
      optional: true,
      reloadProps: true,
      default: false,
    },
  },
  additionalProps() {
    if (this.reRunEnabled) {
      return {
        reRunTimeoutInSecs: {
          type: "integer",
          label: "Rerun Timeout",
          description: "The time in seconds to wait before rerunning the step to retrieve the request response. Eg. `30`. [See the documentation](https://pipedream.com/docs/code/nodejs/rerun/#flowrerun).",
          optional: true,
          min: 10,
        },
      };
    }

    return {
      falWebhook: {
        type: "string",
        label: "Webhook URL",
        description: "The URL to receive updates via webhook.",
        optional: true,
      },
    };
  },
  methods: {
    addToQueue({
      appId, ...args
    } = {}) {
      return this.app.post({
        path: `/${appId}`,
        ...args,
      });
    },
  },
  async run({ $ }) {
    const {
      context: {
        run: {
          runs,
          callback_request: callbackRequest,
        },
      },
    } = $;

    const {
      app,
      addToQueue,
      appId,
      data,
      falWebhook,
      reRunEnabled,
      reRunTimeoutInSecs,
    } = this;

    if (!reRunEnabled) {
      const response = await addToQueue({
        $,
        appId,
        params: {
          fal_webhook: falWebhook,
        },
        data,
      });

      $.export("$summary", `Successfully added the request to the queue with ID \`${response.request_id}\`.`);
      return response;
    }

    if (runs === 1) {
      const timeout = 1000 * (reRunTimeoutInSecs || 10);
      const { resume_url: resumeUrl } = $.flow.rerun(timeout, null, 1);

      return addToQueue({
        $,
        appId,
        params: {
          fal_webhook: resumeUrl,
        },
        data,
      });
    }

    const response = await app.getRequestResponse({
      $,
      appId,
      requestId: callbackRequest.body?.request_id,
    });

    $.export("$summary", "Successfully retrieved the request response.");
    return response;
  },
};

Configuration

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.
LabelPropTypeDescription
fal.aiappappThis component uses the fal.ai app.
App IDappIdstring

The unique identifier for the app. Eg. lora.

Datadataobject

Additional data to include with the request. See the documentation for more input fields.

Rerun EnabledreRunEnabledboolean

Enable the step to rerun to retrieve the request response. See the documentation.

Authentication

fal.ai uses API keys for authentication. When you connect your fal.ai account, Pipedream securely stores the keys so you can easily authenticate to fal.ai APIs in both code and no-code steps.

About fal.ai

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